Sun Wendy, Billot Anne, Du Jingnan, Wei Xiangyu, Lemley Rachel A, Daneshzand Mohammad, Nummenmaa Aapo, Buckner Randy L, Eldaief Mark C
Division of Medical Sciences, Harvard Medical School, Boston, Massachusetts, USA.
Dept. of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, USA.
Hum Brain Mapp. 2025 Aug 1;46(11):e70266. doi: 10.1002/hbm.70266.
Higher-order cognitive and affective functions are supported by large-scale networks in the brain. Dysfunction in different networks is proposed to associate with distinct symptoms in neuropsychiatric disorders. However, the specific networks targeted by current clinical transcranial magnetic stimulation (TMS) approaches are unclear. While standard-of-care TMS relies on scalp-based landmarks, recent FDA-approved TMS protocols use individualized functional connectivity with the subgenual anterior cingulate cortex (sgACC) to optimize TMS targeting. Leveraging previous work on precision network estimation and modeling of the TMS electric field (E-field), we asked whether various clinical TMS approaches target different functional networks between individuals. Results revealed that modeled homotopic scalp positions (left F3 and right F4) target different networks within and across individuals, and right F4 generally favors a right-lateralized control network. TMS coil positions over the dorsolateral prefrontal cortex (dlPFC) zone anticorrelated with the sgACC most frequently target a network coupled to the ventral striatum (reward circuitry) but largely miss that network in some individuals. We further illustrate how modeling can be used to retrospectively assess the estimated targets achieved in prior TMS sessions and also used to prospectively provide coil positions that can target distinct closely localized dlPFC network regions with spatial selectivity and maximal E-field intensity. In a final study, precision targeting was found to be feasible in participants with Major Depressive Disorder using data derived from a single low-burden MRI session suggesting the methods are applicable to translational efforts where limiting patient burden and ensuring robustness are critical.
大脑中的高阶认知和情感功能由大规模网络支持。不同网络的功能障碍被认为与神经精神疾病的不同症状相关。然而,目前临床经颅磁刺激(TMS)方法所针对的具体网络尚不清楚。虽然标准护理TMS依赖于基于头皮的标志物,但最近美国食品药品监督管理局(FDA)批准的TMS方案使用与膝下前扣带回皮质(sgACC)的个体化功能连接来优化TMS靶点。利用先前关于TMS电场(E场)的精确网络估计和建模的工作,我们研究了各种临床TMS方法是否针对个体之间不同的功能网络。结果显示,模拟的同位头皮位置(左F3和右F4)在个体内部和个体之间针对不同的网络,并且右F4通常倾向于右侧化的控制网络。背外侧前额叶皮质(dlPFC)区域上方的TMS线圈位置与sgACC呈反相关,最常针对与腹侧纹状体(奖赏回路)耦合的网络,但在一些个体中很大程度上未命中该网络。我们进一步说明了如何使用建模来回顾性评估先前TMS治疗中实现的估计靶点,还可用于前瞻性地提供能够以空间选择性和最大E场强度靶向不同紧密定位的dlPFC网络区域的线圈位置。在一项最终研究中,发现使用来自单次低负荷MRI检查的数据,对重度抑郁症患者进行精确靶向是可行的,这表明这些方法适用于限制患者负担和确保稳健性至关重要的转化研究。